2021/11/15 – Intel + Lenovo
Coastal Computing
Coastal Computing
Our research into real-time erosion predictions using XBeach was featured in a recent video by Lenovo and CNN. Jessica Gorski describes how we are exploring the use of 1D transect models to predict erosion during storms.
Lenovo provides hardware and support for the HPC services at NC State. The video was produced as branded content for CNN, and it was featured on the CNN web site and social media.
The video required two days of shooting with a team of directors, photographers, audio specialists, and production assistants. Click below to see photos of the production.
Barrier islands are a primary coastal defense and often experience erosion during storms. When they fail due to storm-induced breaching, there can be significant changes to the small- and large-scale hydrodynamics and morphodynamics of the region. In this study, we explore the formation of a breach on Hatteras Island, North Carolina, during Isabel (2003) and the subsequent flooding into Pamlico Sound. Two-way coupling of high-fidelity, high-resolution numerical models for coastal erosion and flooding enables a better understanding of the formation of the breach, as well as scenarios of the breach’s effects on the circulation in the region. The breach connecting the ocean to the sound formed during the day of landfall. It is shown that, during the storm, overwash and inundation from the ocean led to deterioration of the beach and dunes, and then after the storm, the creation of channels through the island was sensitive to elevated water levels in the lagoon. Then flooding scenarios are considered in which the ground surface of the hydrodynamic model was (a) static, updated with the (b) pre- and post-storm observations, and updated dynamically with (c) erosion model predictions and (d) erosion model predictions with elevated lagoon-side water levels. The model results show that the breach has region-scale effects on flooding that extend 10 to 13 km into the lagoon, increasing the local water levels by as much as 1.5 m. These results have implications for similar island-lagoon systems threatened by storms.
Coastal flooding models are used to predict the timing and magnitude of inundation during storms, both for real-time forecasting and long-term design. However, there is a need for faster flooding predictions that also represent flow pathways and barriers at the scales of critical infrastructure. This need can be addressed via subgrid corrections, which use information at smaller scales to ‘correct’ the flow variables (water levels, current velocities) averaged over the mesh scale. Recent studies have shown a decrease in run time by 1 to 2 orders of magnitude, with the ability to decrease further if the model time step is also increased. In this study, subgrid corrections are added to a widely used, finite-element-based, shallow water model to better understand how they can improve the accuracy and efficiency of inundation predictions. The performance of the model, with and without subgrid corrections, is evaluated on scenarios of tidal flooding in a synthetic domain and a small bay in Massachusetts, as well as a scenario with a real atmospheric forcing and storm surge in southwest Louisiana. In these tests we observed that the subgrid corrections can increase model speed by 10 to 50 times, while still representing flow through channels below the mesh scale to inland locations.
Hurricanes are devastating natural hazards that often cause damage to the built environment as a result of their loadings, which include storm surge, waves, and wind, often in combination. Modeling these hazards individually and their effects on buildings is a complex process because each loading component within the hazard behaves differently, affecting either the building envelope, the structural system, or the interior contents. Realistic modeling of hurricane effects requires a multihazard approach that considers the combined effects of wind, surge, and waves. Previous studies focused primarily on modeling these hazards individually, with less focus on the multihazard impact on the whole building system made up of the combination of the structure and its interior contents. The analysis resolution used in previous studies did not fully enable hurricane risk assessment through a detailed investigation of the vulnerability at the component-level or subassembly-level (a group of components such as interior contents, structural components, or nonstructural components). To address these research gaps, a robust multihazard hurricane risk analysis model that uses high-resolution hazard, exposure, and vulnerability models was developed. This model uses a novel approach to combine the storm surge and wave fragility functions with a suite of existing wind fragilities to account for structural damage and then combines them with another suite of flood-based fragilities to account for interior content damage. The proposed vulnerability model was applied to the state of North Carolina as an example of a regional-scale assessment to demonstrate the ability of the method to predict damage at the building level across this large spatial domain. This model enables better understanding of the damages caused by hurricanes in coastal regions, thereby setting initial post-impact conditions for community resilience assessment and investigation of recovery policy alternatives.
